I
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t
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na
l J
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Adv
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nces in Applie
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s
(
I
J
AAS)
Vo
l.
13
,
No
.
4
,
Dec
em
b
er
2
0
2
4
,
p
p
.
8
0
0
~
80
9
I
SS
N:
2252
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8
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1
4
,
DOI
:
1
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1
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v13.
i
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pp
800
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I
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W
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tili
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o
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s
y
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is
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to
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th
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PV
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,
p
ar
ticu
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ly
as
s
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tr
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s
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ab
le
an
d
r
en
ewa
b
le
en
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g
y
s
o
u
r
ce
[
1
]
.
So
il
d
ep
o
s
itio
n
o
n
s
o
lar
m
o
d
u
les
o
cc
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wh
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d
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an
d
elec
tr
icity
g
e
n
er
ati
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n
ca
p
ab
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[
2
]
.
Facto
r
s
lik
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win
d
,
r
ain
,
o
r
h
u
m
an
ac
tiv
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co
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ib
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te
to
th
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s
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ac
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m
u
latio
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.
R
ed
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ce
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s
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ac
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ar
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co
v
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ed
in
d
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an
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d
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[
3
]
,
r
esu
ltin
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in
d
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s
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g
y
o
u
tp
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t,
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d
in
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r
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s
ed
m
ain
ten
an
ce
co
s
ts
f
o
r
th
e
s
y
s
tem
[
4
]
.
T
h
e
o
u
tp
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t
o
f
s
o
lar
PV
p
an
el
s
is
af
f
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ted
b
y
p
a
r
am
eter
s
s
u
ch
as
p
r
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ip
itatio
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,
win
d
an
g
le,
am
b
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t
tem
p
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r
e,
win
d
s
p
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,
tr
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s
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.
As
th
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p
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talled
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s
a
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ex
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atm
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th
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ac
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m
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latio
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f
s
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if
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lead
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d
is
r
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p
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s
in
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p
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en
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[
5
]
.
So
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s
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o
f
tr
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p
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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Ap
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l Sci
I
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N:
2252
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8
8
1
4
Mo
d
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g
s
o
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s
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n
p
r
ed
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n
s
o
n
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(
Mu
h
a
mma
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A
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A
min
Mu
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a
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S
u
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)
801
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eg
r
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,
a
n
d
s
u
b
s
eq
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en
t
p
o
wer
lo
s
s
es
[
6
]
,
[
7
]
.
Sev
e
r
al
s
tu
d
ies
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av
e
in
v
esti
g
ated
th
e
im
p
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o
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s
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o
lar
PV
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y
s
te
m
s
.
Fo
r
in
s
tan
ce
,
J
aszcz
u
r
et
a
l
.
[
8
]
co
n
d
u
cted
a
n
u
m
er
ic
al
s
im
u
latio
n
s
tu
d
y
f
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s
in
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o
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d
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t
ac
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m
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o
n
PV
p
an
els
in
r
eg
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s
with
h
ig
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lev
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p
ar
ticu
lar
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y
f
o
r
p
an
els
u
s
ed
in
s
tr
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t
lig
h
t
p
o
s
ts
.
I
n
a
s
im
ilar
v
ein
,
Fer
n
á
n
d
ez
-
So
las
et
a
l
.
[
9
]
p
r
o
p
o
s
ed
f
iv
e
an
a
ly
tical
tech
n
iq
u
es
to
p
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d
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-
tim
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o
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n
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d
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h
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n
to
m
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ate
d
u
s
t
ac
cu
m
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latio
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.
Wu
et
a
l
.
[
1
0
]
p
r
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p
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s
ed
a
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u
m
er
ical
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im
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latio
n
m
eth
o
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to
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o
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el
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m
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n
a
n
d
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aly
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ts
o
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v
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o
n
s
tr
atin
g
its
ef
f
ec
tiv
en
ess
in
m
an
ag
in
g
s
o
ilin
g
in
win
d
y
en
v
i
r
o
n
m
e
n
ts
.
W
h
ile,
Po
lo
et
a
l
.
[
1
1
]
p
r
ed
icted
s
o
i
lin
g
lo
s
s
to
ad
d
r
ess
its
im
p
ac
t
o
n
s
o
lar
en
er
g
y
o
u
tp
u
t,
ev
alu
atin
g
th
ei
r
m
o
d
el
s
u
s
in
g
d
ata
f
r
o
m
th
e
PVLib
p
ac
k
ag
e
an
d
test
in
g
u
n
d
er
s
u
m
m
er
c
o
n
d
itio
n
s
in
Ma
d
r
id
.
Ad
d
itio
n
ally
,
Pér
ez
e
t
a
l
.
[
1
2
]
p
r
o
p
o
s
ed
an
ar
tific
ia
l
in
tellig
en
ce
m
o
d
el
f
o
r
p
r
e
d
i
ctin
g
en
er
g
y
lo
s
s
es
d
u
e
to
s
o
il
d
ep
o
s
itio
n
o
n
s
o
l
ar
p
a
n
els,
in
co
r
p
o
r
atin
g
m
ete
o
r
o
lo
g
ical
f
ac
to
r
s
an
d
elec
tr
i
ca
l
p
ar
am
eter
s
in
to
th
eir
m
o
d
el.
Alth
o
u
g
h
e
x
is
tin
g
liter
atu
r
e
la
y
s
th
e
g
r
o
u
n
d
wo
r
k
f
o
r
s
tu
d
y
i
n
g
s
o
il
d
ep
o
s
itio
n
p
r
ed
ictio
n
m
o
d
els,
f
ew
s
tu
d
ies
u
s
e
ar
tific
ial
n
eu
r
al
n
etwo
r
k
(
ANN
)
m
eth
o
d
s
f
o
r
t
h
is
p
u
r
p
o
s
e.
Mo
s
t
r
esear
ch
f
o
cu
s
es
o
n
co
u
n
tr
ies
with
s
ea
s
o
n
al
clim
ates,
o
v
er
l
o
o
k
in
g
r
eg
i
o
n
s
with
co
n
s
is
te
n
t
clim
ates
lik
e
Ma
lay
s
ia.
T
h
er
e
is
also
a
lack
o
f
an
aly
s
is
o
n
h
o
w
m
eteo
r
o
lo
g
i
ca
l
f
ac
to
r
s
in
Ma
lay
s
ia
af
f
ec
t
s
o
ilin
g
ac
cu
m
u
latio
n
,
h
ig
h
li
g
h
tin
g
th
e
n
ee
d
f
o
r
f
u
r
th
er
i
n
v
esti
g
atio
n
.
R
esear
ch
in
th
is
ar
ea
co
u
ld
im
p
r
o
v
e
p
r
e
d
ictiv
e
m
ain
ten
a
n
ce
an
d
r
e
d
u
ce
o
p
er
atio
n
an
d
m
ain
ten
an
ce
co
s
ts
f
o
r
s
o
lar
PV
in
s
talla
tio
n
s
.
B
y
ex
am
in
in
g
th
e
r
elatio
n
s
h
ip
s
b
etwe
en
v
ar
ia
b
les
s
u
ch
as
p
r
ec
ip
itatio
n
,
win
d
an
g
le,
tem
p
er
atu
r
e
,
win
d
s
p
ee
d
,
tr
an
s
ien
t
ir
r
ad
iatio
n
,
an
d
s
o
il
d
ep
o
s
itio
n
,
an
ANN
m
o
d
el
ca
n
p
r
ed
ict
s
o
il
d
ep
o
s
itio
n
u
n
d
e
r
d
if
f
er
e
n
t
co
n
d
itio
n
s
.
T
h
is
s
tu
d
y
aim
s
to
en
h
an
ce
PV
s
y
s
tem
p
er
f
o
r
m
an
c
e
b
y
m
itig
atin
g
s
o
il
d
ep
o
s
itio
n
,
th
u
s
in
c
r
ea
s
in
g
e
f
f
icien
cy
an
d
r
ed
u
cin
g
elec
tr
icit
y
p
r
o
d
u
ctio
n
co
s
ts
[
3
]
.
Ad
d
itio
n
ally
,
ad
d
r
ess
in
g
p
an
el
clea
n
in
g
co
s
ts
co
u
ld
lo
wer
m
ain
ten
an
ce
ex
p
en
s
es.
T
h
e
ANN
m
o
d
el
will
b
e
tr
ain
ed
with
v
ar
io
u
s
m
eteo
r
o
lo
g
ical
v
ar
iab
les
to
u
n
d
er
s
tan
d
th
ei
r
im
p
ac
t
o
n
s
o
il
in
g
d
ep
o
s
itio
n
.
A
m
u
lti
-
v
ar
ia
b
le
lin
ea
r
r
e
g
r
ess
io
n
(
ML
R
)
m
o
d
el
will b
e
u
s
ed
t
o
ass
es
s
th
e
ANN
m
o
d
el'
s
ac
cu
r
ac
y
.
T
h
e
p
ap
er
is
s
tr
u
ctu
r
e
d
as
f
o
llo
ws.
I
n
s
ec
tio
n
2
,
we
d
escr
ib
e
th
e
o
v
er
all
f
r
am
ewo
r
k
a
n
d
s
y
s
tem
ar
ch
itectu
r
e
o
f
th
e
s
o
il
d
e
p
o
s
itio
n
p
r
ed
ictio
n
m
o
d
el
an
d
th
e
in
f
lu
en
ce
o
f
in
p
u
t
p
a
r
am
eter
s
esti
m
a
tio
n
u
s
in
g
g
lo
b
al
s
en
s
itiv
ity
an
aly
s
is
(
GSA
)
.
I
n
s
ec
ti
o
n
3
,
th
e
r
esu
lts
o
f
th
e
b
est
ANN
m
o
d
el
ar
c
h
itectu
r
e
ar
e
p
r
esen
te
d
,
alo
n
g
with
an
ev
alu
atio
n
o
f
th
e
p
ar
am
eter
s
th
at
m
o
s
t
s
i
g
n
if
ican
tly
af
f
ec
t
t
h
e
m
o
d
el.
Fin
ally
,
se
ctio
n
4
p
r
o
v
id
es th
e
co
n
clu
s
io
n
o
f
t
h
e
s
tu
d
y
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
2
.
1
.
O
v
er
a
ll
m
et
ho
do
lo
g
y
f
r
a
m
ewo
r
k
Fig
u
r
e
1
illu
s
tr
ates
a
th
o
r
o
u
g
h
f
lo
wch
ar
t
o
f
th
e
p
r
o
ject.
I
n
o
r
d
er
to
ch
o
o
s
e
th
e
m
o
s
t
s
u
itab
le
ty
p
e
o
f
d
ata
f
o
r
th
is
p
r
o
ject,
s
im
p
lific
atio
n
o
f
th
e
p
r
o
ject'
s
s
co
p
e
is
en
tailed
in
th
e
d
ata
-
g
ath
er
in
g
p
r
o
ce
d
u
r
e.
T
h
e
g
o
al
o
f
th
is
p
r
o
ject
is
to
u
s
e
ANN
to
esti
m
ate
th
e
s
o
ilin
g
r
ate
o
f
s
o
lar
PV
p
an
els.
T
o
cr
ea
te
an
ANN
ar
ch
itectu
r
e
f
o
r
esti
m
atin
g
s
o
ilin
g
r
ate,
d
ata
in
clu
d
in
g
p
r
ec
ip
itatio
n
,
win
d
an
g
le,
am
b
ie
n
t
tem
p
e
r
atu
r
e,
win
d
s
p
ee
d
,
tr
an
s
ien
t
ir
r
ad
iatio
n
,
a
n
d
p
o
wer
g
en
er
ated
wer
e
m
ea
s
u
r
ed
.
I
n
t
h
e
s
u
b
s
eq
u
e
n
t
s
tep
,
th
e
m
ea
n
a
b
s
o
lu
te
p
er
ce
n
tag
e
e
r
r
o
r
(
MA
PE)
,
d
e
ter
m
in
in
g
th
e
p
er
ce
n
tag
e
er
r
o
r
o
f
th
e
m
o
d
el'
s
n
u
m
er
ical
esti
m
ates,
an
d
th
e
co
ef
f
icien
t
o
f
d
eter
m
i
n
atio
n
(R
2
)
,
in
d
icatin
g
th
e
lin
ea
r
r
elatio
n
s
h
ip
b
etwe
en
ex
p
er
im
e
n
tal
an
d
s
im
u
lated
d
ata,
s
er
v
ed
as
th
e
m
ath
em
atica
l
er
r
o
r
cr
iter
ia
f
o
r
co
m
p
a
r
in
g
an
d
o
b
tain
in
g
s
tatis
tical
co
m
p
ar
is
o
n
s
o
f
th
e
ANN
m
o
d
els
.
Fin
ally
,
th
e
co
n
d
itio
n
al
an
d
u
n
co
n
d
itio
n
al
cu
m
u
lati
v
e
d
is
tr
ib
u
tio
n
f
u
n
ctio
n
s
(
C
DFs
)
wer
e
em
p
lo
y
e
d
b
etwe
en
th
e
p
a
r
tially
ad
d
itiv
e
an
d
p
a
r
tially
n
o
n
lin
ea
r
(
P
AW
N
)
s
en
s
it
iv
ity
an
aly
s
is
as
a
m
ea
s
u
r
em
en
t
o
f
d
is
tan
ce
d
u
e
to
its
lo
w
co
m
p
u
t
atio
n
al
co
s
t a
n
d
ef
f
ec
tiv
e
o
u
tco
m
es f
o
r
n
o
n
lin
ea
r
co
m
p
u
tatio
n
al
m
o
d
els
[
1
3
]
.
Fig
u
r
e
1
.
Flo
wch
ar
t
o
f
r
esear
c
h
m
eth
o
d
o
lo
g
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
1
4
I
n
t J Ad
v
Ap
p
l Sci
,
Vo
l.
13
,
No
.
4
,
Dec
em
b
er
2
0
2
4
:
800
-
8
0
9
802
2
.
2
.
Art
if
ici
a
l neura
l net
wo
rk
mo
delin
g
pro
ce
s
s
2
.
2
.
1
.
Da
t
a
a
cquis
it
io
n
a
nd
p
re
-
pro
ce
s
s
ing
ANN
s
o
il
p
r
ed
ictio
n
m
o
d
el
was
d
ev
elo
p
ed
f
o
r
a
s
o
lar
f
a
r
m
lo
ca
ted
in
th
e
ce
n
tr
al
o
f
Pen
in
s
u
lar
Ma
lay
s
ia.
T
o
id
en
tify
th
e
s
o
ilin
g
r
ate
o
v
er
tim
e,
p
o
wer
g
en
er
ated
at
th
e
in
v
e
r
ter
was
r
ec
o
r
d
ed
.
T
h
e
estab
lis
h
ed
wea
th
er
s
tatio
n
th
er
e
was
u
s
ed
to
co
llect
th
e
r
e
m
ain
in
g
d
ata.
I
n
t
h
e
p
r
e
-
p
r
o
ce
s
s
in
g
p
ar
t
o
f
th
e
s
o
il
d
ep
o
s
itio
n
p
r
ed
ictio
n
m
o
d
el,
th
e
d
ata
is
p
r
ep
a
r
ed
an
d
p
r
o
ce
s
s
ed
to
en
s
u
r
e
its
q
u
ality
an
d
s
u
itab
ilit
y
f
o
r
tr
ain
in
g
th
e
ANN
m
o
d
el.
T
h
e
co
llected
d
ata
is
ex
am
in
ed
f
o
r
m
is
s
in
g
v
alu
es,
o
u
tlier
s
,
an
d
in
co
n
s
is
ten
cies.
Miss
in
g
v
alu
es
ca
n
b
e
h
an
d
led
b
y
im
p
u
tatio
n
tech
n
iq
u
es,
s
u
ch
as
m
ea
n
o
r
m
ed
ian
s
u
b
s
titu
tio
n
,
o
r
u
s
in
g
ad
v
an
ce
d
m
eth
o
d
s
lik
e
r
e
g
r
ess
io
n
-
b
ased
im
p
u
tatio
n
.
Ou
tlier
s
c
an
b
e
id
en
tifie
d
an
d
tr
ea
ted
b
ased
o
n
s
tatis
tical
tech
n
iq
u
es o
r
d
o
m
ain
k
n
o
wle
d
g
e.
C
o
r
r
elatio
n
an
al
y
s
is
h
elp
s
to
u
n
d
er
s
tan
d
th
e
r
elatio
n
s
h
i
p
s
b
etwe
en
d
if
f
er
en
t
m
eteo
r
o
lo
g
ical
f
ac
to
r
s
an
d
s
o
il
d
ep
o
s
itio
n
.
Var
ia
b
les
th
at
e
x
h
ib
it
a
h
ig
h
c
o
r
r
elatio
n
with
s
o
il
d
ep
o
s
itio
n
a
r
e
ty
p
ically
r
etain
ed
f
o
r
m
o
d
el
tr
ain
in
g
.
2
.
2
.
2
.
So
ilin
g
ra
t
e
c
a
lcula
t
io
n
T
h
e
p
o
wer
g
en
er
ated
b
y
a
s
o
l
ar
PV
s
y
s
tem
is
d
ir
ec
tly
r
elat
ed
to
th
e
in
te
n
s
ity
o
f
s
u
n
lig
h
t
f
allin
g
o
n
th
e
p
an
els.
As
s
o
il
ac
c
u
m
u
la
tes
o
n
th
e
p
an
el
s
u
r
f
ac
e,
it
ac
ts
as
a
b
ar
r
ier
,
r
e
d
u
cin
g
th
e
tr
an
s
m
ittan
ce
o
f
s
u
n
lig
h
t
th
r
o
u
g
h
th
e
p
an
el.
T
h
is
r
esu
lts
in
a
lo
wer
am
o
u
n
t
o
f
s
u
n
lig
h
t
b
ein
g
co
n
v
er
ted
in
t
o
elec
tr
icity
b
y
th
e
PV
ce
lls
,
th
er
eb
y
r
ed
u
cin
g
th
e
p
o
wer
g
en
e
r
ated
.
T
h
e
r
elatio
n
s
h
ip
b
etwe
en
p
o
wer
g
e
n
er
ated
an
d
s
o
ilin
g
r
ate
i
n
s
o
lar
PV
s
y
s
tem
s
is
b
ased
o
n
th
e
im
p
ac
t
o
f
s
o
ilin
g
o
n
th
e
ef
f
icien
cy
o
f
t
h
e
p
a
n
el
s
.
So
ilin
g
,
o
r
th
e
ac
cu
m
u
latio
n
o
f
d
ir
t a
n
d
d
u
s
t o
n
th
e
p
an
el
s
u
r
f
ac
e
,
r
ed
u
ce
s
t
h
e
am
o
u
n
t o
f
s
u
n
lig
h
t r
ea
ch
i
n
g
th
e
PV
ce
lls
.
T
h
i
s
r
ed
u
ctio
n
in
s
u
n
lig
h
t
ab
s
o
r
p
tio
n
lead
s
to
a
d
ec
r
ea
s
e
in
p
o
w
er
o
u
tp
u
t
f
r
o
m
th
e
PV
s
y
s
tem
.
T
h
e
s
o
ilin
g
r
ate
is
ca
lcu
lated
u
s
in
g
(
1
)
an
d
(
2
)
.
=
(
1
)
=
−
=
ⅈ
72
(
2
)
W
h
er
e
G
is
r
ec
eiv
ed
i
r
r
ad
ian
c
e
b
y
th
e
s
o
lar
PV
g
las
s
,
P
is
p
o
we
r
g
en
er
ate
d
,
A
is
ar
ea
,
G
m
o
y
is
tr
an
s
m
itted
ir
r
ad
ian
ce
b
y
th
e
s
o
lar
PV
g
l
ass
,
G
i
is
r
eg
u
lar
ly
m
ea
s
u
r
ed
b
y
th
e
s
o
lar
PV
g
lass
,
*
7
2
is
No
o
f
elem
en
ta
r
y
r
ec
tan
g
les o
f
eq
u
al
d
im
en
s
io
n
s
,
G
i
an
d
G
b
o
th
h
av
e
b
ee
n
m
ea
s
u
r
ed
u
s
in
g
a
s
o
lar
p
o
wer
m
eter
.
2
.
2
.
3
.
Art
if
icia
l neura
l net
wo
rk
a
rc
hite
ct
ures des
ig
n a
nd
t
ra
ini
ng
T
h
e
esti
m
atio
n
o
f
f
u
n
ctio
n
s
th
at
h
av
e
m
an
y
p
ar
am
eter
v
a
r
iab
les
is
s
u
itab
le
to
b
e
m
o
d
eled
u
s
in
g
ANN.
An
ANN
n
eu
r
o
n
ass
ig
n
s
th
e
ap
p
r
o
p
r
iate
weig
h
tin
g
f
ac
to
r
(
W
)
to
ea
ch
in
p
u
t
p
ar
am
eter
.
A
tr
an
s
f
er
f
u
n
ctio
n
'
s
o
u
tp
u
t
v
alu
e,
wh
ich
is
d
er
iv
ed
f
r
o
m
th
e
b
ias
(
b
)
a
n
d
weig
h
te
d
in
p
u
ts
s
u
m
m
ed
t
o
g
eth
er
,
in
f
lu
e
n
ce
s
h
o
w
n
ea
r
b
y
n
e
u
r
o
n
s
r
ea
ct
[
5
]
.
An
in
p
u
t
la
y
er
,
a
h
id
d
en
lay
e
r
o
r
lay
e
r
s
,
an
d
a
n
o
u
tp
u
t
lay
e
r
ty
p
ically
m
ak
e
u
p
an
ANN'
s
ar
ch
itectu
r
e.
T
o
ad
d
r
ess
th
e
n
o
n
-
lin
ea
r
m
u
ltiv
ar
i
ab
le
is
s
u
e,
ANN
g
o
es
th
r
o
u
g
h
an
iter
ativ
e
tr
ain
in
g
p
h
ase.
T
o
ca
r
r
y
o
u
t
th
is
p
r
o
ce
s
s
,
ce
r
tain
alg
o
r
ith
m
s
ar
e
u
s
ed
,
with
th
e
B
ac
k
-
Pro
p
ag
atio
n
a
lg
o
r
ith
m
b
ein
g
o
n
e
o
f
th
e
m
o
st
u
s
ed
o
n
es
[
1
4
]
.
I
n
th
is
p
ap
er
,
s
ev
er
al
ANN
a
r
ch
itectu
r
es
wer
e
e
v
alu
ated
to
id
en
tify
a
m
o
d
el
th
at
ac
cu
r
ate
ly
p
r
e
d
icts
th
e
r
ate
o
f
PV
g
lass
s
o
ilin
g
.
F
ig
u
r
e
2
d
ep
icts
th
e
b
asic
ANN
ar
ch
itectu
r
e,
wh
ich
co
m
p
r
is
es
o
n
e
n
eu
r
o
n
in
th
e
o
u
tp
u
t
la
y
er
an
d
f
i
v
e
n
e
u
r
o
n
s
in
th
e
i
n
p
u
t
la
y
er
,
wh
ic
h
s
tan
d
in
f
o
r
th
e
p
r
ec
ip
itatio
n
,
w
in
d
an
g
le,
am
b
ie
n
t
tem
p
er
atu
r
e,
win
d
s
p
ee
d
,
a
n
d
tr
an
s
ien
t
ir
r
ad
iatio
n
.
T
h
e
tr
an
s
f
er
f
u
n
ctio
n
s
u
tili
ze
d
f
o
r
n
o
n
li
n
ea
r
s
o
lu
tio
n
s
ar
e
th
e
lin
ea
r
tr
a
n
s
f
er
f
u
n
ctio
n
f
o
r
th
e
o
u
tp
u
t
lay
er
an
d
th
e
h
y
p
er
b
o
lic
tan
g
e
n
t
s
ig
m
o
id
f
o
r
th
e
h
id
d
en
lay
er
.
E
x
p
lain
in
g
r
esear
ch
c
h
r
o
n
o
l
o
g
ical
ly
,
in
clu
d
in
g
r
esear
ch
d
esig
n
,
r
esear
ch
p
r
o
ce
d
u
r
e
(
in
th
e
f
o
r
m
o
f
alg
o
r
ith
m
s
,
Ps
eu
d
o
co
d
e
,
o
r
o
t
h
er
)
,
h
o
w
to
test
,
an
d
d
ata
ac
q
u
is
itio
n
[
1
5
]
–
[
1
7
]
.
T
h
e
d
escr
ip
tio
n
o
f
th
e
co
u
r
s
e
o
f
r
esear
ch
s
h
o
u
ld
b
e
s
u
p
p
o
r
t
ed
by
r
ef
er
e
n
ce
s
,
s
o
th
e
ex
p
lan
atio
n
ca
n
b
e
ac
ce
p
ted
s
cien
tific
ally
[
1
8
]
,
[
1
9
]
.
Fig
u
r
e
2
an
d
T
ab
le
1
ar
e
p
r
esen
ted
ce
n
ter
,
as sh
o
w
n
b
elo
w
a
n
d
cited
in
t
h
e
m
an
u
s
cr
ip
t
[
1
5
]
,
[
2
0
]
–
[
2
5
]
.
A
f
u
n
ctio
n
in
g
d
atab
ase
was
m
ad
e
f
o
r
s
o
il
d
ep
o
s
itio
n
o
n
PV
pa
n
els,
p
r
ec
ip
itatio
n
,
win
d
an
g
le,
am
b
ien
t
tem
p
er
at
u
r
e,
win
d
s
p
ee
d
,
an
d
tr
an
s
ien
t
ir
r
a
d
iatio
n
u
s
in
g
th
e
d
ata
th
at
th
e
m
ea
s
u
r
em
en
t
eq
u
ip
m
en
t
co
llected
b
ased
o
n
T
ab
l
e
1
.
T
h
e
d
atab
ase
was
r
an
d
o
m
ly
d
iv
id
ed
in
to
th
r
ee
d
i
f
f
er
en
t
p
ar
ts
f
o
r
th
e
ANN
tr
ain
in
g
p
r
o
ce
s
s
:
8
0
%
wen
t
to
th
e
tr
ain
in
g
p
h
ase,
1
0
%
to
th
e
v
alid
atio
n
p
h
ase,
a
n
d
1
0
%
t
o
th
e
test
in
g
p
h
ase.
T
h
e
r
an
d
o
m
d
iv
is
io
n
ap
p
r
o
ac
h
was u
s
ed
to
m
ak
e
s
u
r
e
t
h
at
th
e
d
ata
d
is
tr
ib
u
tio
n
was a
cc
u
r
ately
ap
p
r
o
x
im
ated
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ad
v
Ap
p
l Sci
I
SS
N:
2252
-
8
8
1
4
Mo
d
ellin
g
s
o
il d
ep
o
s
itio
n
p
r
ed
ictio
n
s
o
n
s
o
la
r
…
(
Mu
h
a
mma
d
A
ima
n
A
min
Mu
h
a
mma
d
S
u
h
a
imi
)
803
Fig
u
r
e
2
.
ANN
ar
ch
itectu
r
e
f
o
r
s
o
ilin
g
r
ate
esti
m
atio
n
T
ab
l
e
1
.
Par
am
eter
s
u
s
ed
f
o
r
t
h
e
m
ath
em
atica
l m
o
d
elin
g
p
r
o
ce
s
s
P
a
r
a
me
t
e
r
s
M
i
n
M
a
x
U
n
i
t
s
I
n
p
u
t
s
P
r
e
c
i
p
i
t
a
t
i
o
n
0
.
2
89
[
mm
]
W
i
n
d
a
n
g
l
e
1
3
5
8
[
°
]
A
mb
i
e
n
t
t
e
m
p
e
r
a
t
u
r
e
2
7
.
5
3
5
.
8
(
℃
)
W
i
n
d
s
p
e
e
d
0
.
1
4
.
1
(
m/
s)
Tr
a
n
s
i
e
n
t
i
r
r
a
d
i
a
t
i
o
n
4
1
2
3
8
(W/
㎡
)
O
u
t
p
u
t
P
V
g
l
a
sses
so
i
l
i
n
g
r
a
t
e
0
.
9
9
2
7
0
.
9
9
9
9
[
%]
2
.
2
.
4
.
Sta
t
is
t
ica
l
co
m
pa
riso
n
o
f
a
rt
if
icia
l neura
l net
wo
r
k
m
o
dels
T
h
e
L
ev
en
b
er
g
-
Ma
r
q
u
ar
d
t
(
L
M)
b
ac
k
p
r
o
p
ag
atio
n
alg
o
r
ith
m
-
a
New
to
n
m
eth
o
d
d
er
iv
ati
o
n
-
is
o
n
e
o
f
th
e
b
est
tech
n
iq
u
es
f
o
r
ac
ce
le
r
atin
g
th
e
co
n
v
er
g
en
ce
o
f
A
NN
s
tr
u
ctu
r
es.
I
t
was
ap
p
lied
to
ch
o
o
s
e
th
e
id
ea
l
b
ias
v
alu
es
an
d
weig
h
ts
.
I
t
o
f
f
er
s
s
im
p
ler
ca
lcu
latio
n
an
d
l
e
s
s
weig
h
ted
er
r
o
r
p
r
o
p
ag
atio
n
th
an
s
y
s
tem
s
with
two
o
r
m
o
r
e
h
id
d
en
la
y
er
s
.
T
h
e
m
ath
em
atica
l
er
r
o
r
cr
iter
ia
u
s
ed
f
o
r
t
h
e
co
m
p
ar
is
o
n
s
wer
e
th
e
MA
PE,
wh
ich
co
m
p
u
tes
th
e
p
er
ce
n
tag
e
er
r
o
r
o
f
t
h
e
m
o
d
el'
s
n
u
m
er
ical
esti
m
ates,
th
e
r
o
o
t
m
ea
n
s
q
u
ar
e
er
r
o
r
(
R
MSE
)
,
wh
ic
h
ass
es
s
es
th
e
v
ar
iatio
n
b
etwe
en
th
e
m
o
d
el'
s
p
r
ed
icted
a
n
d
ex
p
er
im
en
tal
m
ea
s
u
r
es,
a
n
d
th
e
co
ef
f
icien
t
o
f
d
eter
m
in
atio
n
(R
2
)
,
wh
ich
estab
lis
h
es th
e
lin
ea
r
r
elatio
n
s
h
ip
b
etwe
en
ex
p
er
im
e
n
tal
an
d
s
im
u
lated
d
ata.
=
√
(
−
)
2
(
3
)
=
|
−
|
×
100
(
4
)
2
=
1
−
(
−
)
2
(
−
̅
)
2
(
5
)
W
h
er
e
t
is
th
e
m
ea
s
u
r
ed
PV
g
lass
s
o
ilin
g
r
ate
,
y
is
th
e
s
im
u
lated
ANN
o
u
tp
u
t
,
an
d
̅
is
th
e
av
er
ag
e
ex
p
er
im
en
tal
PV g
lass
s
o
ilin
g
r
ate
.
2
.
3
.
G
l
o
ba
l
s
ens
it
iv
it
y
a
na
ly
s
is
T
h
e
in
f
lu
e
n
ce
o
f
ea
c
h
in
p
u
t
p
ar
am
eter
is
esti
m
ated
u
s
in
g
a
s
et
o
f
m
ath
em
atica
l
o
p
er
atio
n
s
k
n
o
wn
as
GSA.
T
o
ev
al
u
ate
th
e
r
elati
o
n
s
h
ip
'
s
f
itn
ess
an
d
th
e
m
o
d
el's
co
n
s
is
ten
cy
with
r
ea
lity
.
T
h
e
Ko
lm
o
g
o
r
o
v
-
Sm
ir
n
o
v
(
KS)
s
tatis
tic
i
s
ap
p
lied
to
co
m
p
ar
e
th
e
v
a
r
iati
o
n
s
b
etwe
en
u
n
co
n
d
itio
n
al
an
d
c
o
n
d
itio
n
al
C
DFs
a
s
in
(
6
)
.
=
ma
x
|
−
|
(
6
)
A
PAW
N
s
en
s
it
iv
ity
in
d
ex
(
T
i)
,
th
at
f
ac
to
r
s
in
to
ac
co
u
n
t
a
s
tatis
tic
o
v
er
all
p
o
ten
tial
v
alu
e
s
o
f
x
i,
is
g
en
er
ated
s
in
ce
KS d
e
p
en
d
s
o
n
th
e
f
ix
e
d
v
alu
e
o
f
x
i
as in
(
7
)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
1
4
I
n
t J Ad
v
Ap
p
l Sci
,
Vo
l.
13
,
No
.
4
,
Dec
em
b
er
2
0
2
4
:
800
-
8
0
9
804
=
[
(
)
]
(
7
)
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
Art
if
ici
a
l neura
l net
wo
rk
–
s
o
il depo
s
it
io
n pre
dict
io
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E
rr
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Ref
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,
5
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d
6
s
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3
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3
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I
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8
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ased
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
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4
I
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v
Ap
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Vo
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13
,
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4
,
Dec
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ased
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u
r
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ased
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ased
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a
n
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iatio
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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Ap
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N:
2252
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4
Mo
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il d
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ed
ictio
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n
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h
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ima
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A
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Mu
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a
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imi
)
807
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ab
l
e
3
.
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elativ
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im
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o
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tan
ce
o
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in
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u
t v
ar
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les f
r
o
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ain
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a
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4
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CO
NCLU
SI
O
N
T
h
e
s
o
ilin
g
r
ate
co
n
ce
r
n
in
g
en
v
ir
o
n
m
en
tal
v
ar
ia
b
les
s
u
ch
as
p
r
ec
ip
itatio
n
,
win
d
a
n
g
le
,
am
b
ien
t
tem
p
er
atu
r
e,
win
d
s
p
ee
d
,
an
d
tr
an
s
ien
t
ir
r
ad
iatio
n
was
ex
p
r
e
s
s
ed
th
r
o
u
g
h
t
h
e
cr
ea
tio
n
o
f
a
n
ANN
m
o
d
el.
T
h
e
m
o
d
el'
s
p
er
f
o
r
m
an
ce
was
ass
ess
ed
u
s
in
g
s
tatis
tica
l
m
ea
s
u
r
es,
co
m
p
ar
in
g
it
to
d
ata
th
a
t
was
n
o
t
u
tili
ze
d
d
u
r
in
g
th
e
m
o
d
elin
g
p
r
o
ce
s
s
.
T
h
e
s
tatis
tical
f
in
d
in
g
s
in
d
icat
e
th
at
th
e
ANN
m
o
d
el
h
as
s
u
f
f
icien
t
ca
p
ab
ilit
y
to
esti
m
ate
u
n
d
er
t
h
e
ca
s
e
s
tu
d
y
'
s
s
p
ec
if
ic
s
et
o
f
co
n
d
itio
n
s
.
T
h
e
r
esu
lts
o
f
th
e
s
en
s
itiv
ity
an
aly
s
is
d
em
o
n
s
tr
ate
d
th
at
ea
ch
p
ar
a
m
eter
s
ig
n
if
ican
tly
in
f
lu
en
ce
s
th
e
m
o
d
el'
s
o
u
tp
u
t,
with
win
d
s
p
ee
d
h
a
v
in
g
t
h
e
g
r
ea
test
im
p
ac
t
,
f
o
llo
wed
b
y
win
d
a
n
g
le,
a
m
b
ien
t
tem
p
er
atu
r
e,
p
r
ec
i
p
itatio
n
,
an
d
tr
an
s
ien
t
ir
r
a
d
iatio
n
.
T
h
e
s
en
s
itiv
ity
s
tu
d
y
also
d
em
o
n
s
tr
ated
h
o
w
th
e
b
e
h
av
io
r
o
f
th
e
m
o
d
el
'
s
o
u
tp
u
t
wo
u
ld
c
h
an
g
e
if
th
e
v
alu
e
o
f
ea
ch
in
p
u
t
p
ar
am
eter
wer
e
v
ar
ied
ac
r
o
s
s
a
wid
e
r
an
g
e
(
f
r
o
m
m
ax
im
u
m
to
m
in
im
u
m
)
.
T
h
e
s
en
s
itiv
ity
an
al
y
s
is
em
p
lo
y
ed
p
r
o
v
ed
to
b
e
an
ef
f
ec
tiv
e
to
o
l
f
o
r
el
u
cid
atin
g
th
e
u
n
d
er
ly
i
n
g
p
h
y
s
ics
o
f
th
e
p
h
en
o
m
en
o
n
with
in
th
e
ANN
m
o
d
el.
T
h
is
ap
p
r
o
ac
h
p
r
esen
ts
a
p
r
o
m
is
in
g
f
r
am
ewo
r
k
f
o
r
ap
p
licatio
n
in
s
m
ar
t
s
en
s
o
r
s
f
o
r
PV
m
o
d
u
l
e
clea
n
in
g
s
y
s
tem
s
,
en
h
an
cin
g
th
e
o
p
er
atio
n
al
ef
f
i
cien
cy
o
f
th
ese
m
o
d
u
les.
Un
d
er
s
tan
d
in
g
th
e
d
y
n
am
ics
o
f
s
o
ilin
g
ac
cu
m
u
latio
n
o
v
er
tim
e
ca
n
f
ac
ilit
ate
th
e
o
p
ti
m
izatio
n
o
f
m
ain
ten
a
n
ce
p
lan
s
an
d
th
e
d
e
v
elo
p
m
e
n
t
o
f
m
o
r
e
ac
cu
r
ate
f
o
r
ec
asti
n
g
m
o
d
els.
ACK
NO
WL
E
DG
E
M
E
NT
W
e
wo
u
ld
lik
e
to
ex
ten
d
o
u
r
s
in
ce
r
e
ap
p
r
ec
iatio
n
to
Un
iv
er
s
iti
T
ek
n
o
lo
g
i
MA
R
A
(
UiT
M)
f
o
r
p
r
o
v
id
i
n
g
u
s
with
th
eir
s
ite
as a
s
tu
d
y
lo
ca
tio
n
.
RE
F
E
R
E
NC
E
S
[
1
]
P
.
A
.
O
w
u
su
a
n
d
S
.
A
s
u
ma
d
u
-
S
a
r
k
o
d
i
e
,
“
A
r
e
v
i
e
w
o
f
r
e
n
e
w
a
b
l
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n
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g
y
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e
s
,
su
s
t
a
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n
a
b
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l
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t
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ssu
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s
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n
d
c
l
i
m
a
t
e
c
h
a
n
g
e
mi
t
i
g
a
t
i
o
n
,
”
C
o
g
e
n
t
E
n
g
i
n
e
e
r
i
n
g
,
v
o
l
.
3
,
n
o
.
1
,
p
.
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1
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7
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9
0
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.
2
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3
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1
9
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6
.
2
0
1
6
.
1
1
6
7
9
9
0
.
[
2
]
M
.
R
.
M
a
g
h
a
mi
,
H
.
H
i
z
a
m
,
C
.
G
o
m
e
s,
M
.
A
.
R
a
d
z
i
,
M
.
I
.
R
e
z
a
d
a
d
,
a
n
d
S
.
H
a
j
i
g
h
o
r
b
a
n
i
,
“
P
o
w
e
r
l
o
ss
d
u
e
t
o
so
i
l
i
n
g
o
n
s
o
l
a
r
p
a
n
e
l
:
a
r
e
v
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e
w
,
”
R
e
n
e
w
a
b
l
e
a
n
d
S
u
s
t
a
i
n
a
b
l
e
E
n
e
rg
y
Re
v
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e
w
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v
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l
.
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p
.
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u
n
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o
i
:
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6
/
j
.
r
ser.
2
0
1
6
.
0
1
.
0
4
4
.
[
3
]
S
mi
t
h
so
n
i
a
n
,
“
A
b
r
i
e
f
h
i
s
t
o
r
y
o
f
so
l
a
r
p
a
n
e
l
s,
”
S
m
i
t
h
so
n
i
a
n
Ma
g
a
zi
n
e
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
a
t
h
t
t
p
s
:
/
/
w
w
w
.
smi
t
h
so
n
i
a
n
ma
g
.
c
o
m
/
sp
o
n
s
o
r
e
d
/
b
r
i
e
f
-
h
i
st
o
r
y
-
s
o
l
a
r
-
p
a
n
e
l
s
-
1
8
0
9
7
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0
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/
(
a
c
c
e
sse
d
M
a
r
.
3
0
,
2
0
2
4
)
.
[
4
]
M
.
V
i
c
t
o
r
i
a
e
t
a
l
.
,
“
S
o
l
a
r
P
V
s i
s
r
e
a
d
y
t
o
p
o
w
e
r
a
s
u
s
t
a
i
n
a
b
l
e
f
u
t
u
r
e
,
”
J
o
u
l
e
,
v
o
l
.
5
,
n
o
.
5
,
p
p
.
1
0
4
1
–
1
0
5
6
,
2
0
2
1
.
[
5
]
M
.
S
.
C
h
o
w
d
h
u
r
y
e
t
a
l
.
,
“
A
n
o
v
e
r
v
i
e
w
o
f
so
l
a
r
p
h
o
t
o
v
o
l
t
a
i
c
p
a
n
e
l
s’
e
n
d
-
of
-
l
i
f
e
m
a
t
e
r
i
a
l
r
e
c
y
c
l
i
n
g
,
”
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n
e
r
g
y
S
t
r
a
t
e
g
y
Re
v
i
e
w
s
,
v
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l
.
2
7
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.
1
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0
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1
,
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n
.
2
0
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0
,
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/
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.
e
sr
.
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0
1
9
.
1
0
0
4
3
1
.
[
6
]
B
.
A
.
N
e
e
d
e
l
m
a
n
,
“
W
h
a
t
a
r
e
so
i
l
s
?
,
”
N
a
t
u
re
E
d
u
c
a
t
i
o
n
,
2
0
1
3
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
a
t
h
t
t
p
s
:
/
/
w
w
w
.
n
a
t
u
r
e
.
c
o
m/
s
c
i
t
a
b
l
e
/
k
n
o
w
l
e
d
g
e
/
l
i
b
r
a
r
y
/
w
h
a
t
-
a
r
e
-
so
i
l
s
-
6
7
6
4
7
6
3
9
/
#
:
~
:
t
e
x
t
=
S
o
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l
(
a
c
c
e
ss
e
d
F
e
b
.
2
2
,
2
0
2
4
)
.
[
7
]
A
.
S
h
a
j
u
a
n
d
R
.
C
h
a
c
k
o
,
“
S
o
i
l
i
n
g
o
f
p
h
o
t
o
v
o
l
t
a
i
c
m
o
d
u
l
e
s
-
r
e
v
i
e
w
,
”
I
O
P
C
o
n
f
e
r
e
n
c
e
S
e
ri
e
s:
Ma
t
e
r
i
a
l
s
S
c
i
e
n
c
e
a
n
d
E
n
g
i
n
e
e
ri
n
g
,
v
o
l
.
3
9
6
,
p
.
0
1
2
0
5
0
,
A
u
g
.
2
0
1
8
,
d
o
i
:
1
0
.
1
0
8
8
/
1
7
5
7
-
8
9
9
X
/
3
9
6
/
1
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0
1
2
0
5
0
.
[
8
]
M
.
Jas
z
c
z
u
r
e
t
a
l
.
,
“
T
h
e
f
i
e
l
d
e
x
p
e
r
i
men
t
s
a
n
d
mo
d
e
l
o
f
t
h
e
n
a
t
u
r
a
l
d
u
st
d
e
p
o
s
i
t
i
o
n
e
f
f
e
c
t
s
o
n
p
h
o
t
o
v
o
l
t
a
i
c
m
o
d
u
l
e
e
f
f
i
c
i
e
n
c
y
,
”
En
v
i
r
o
n
m
e
n
t
a
l
S
c
i
e
n
c
e
a
n
d
P
o
l
l
u
t
i
o
n
Re
se
a
rc
h
,
v
o
l
.
2
6
,
n
o
.
9
,
p
p
.
8
4
0
2
–
8
4
1
7
,
M
a
r
.
2
0
1
9
,
d
o
i
:
1
0
.
1
0
0
7
/
s
1
1
3
5
6
-
0
1
8
-
1
9
7
0
-
x.
[
9
]
Á
.
F
e
r
n
á
n
d
e
z
-
S
o
l
a
s,
J.
M
o
n
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B
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iv
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Tek
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(UiT
M
)
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h
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h
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m
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a
lay
sia
.
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rre
n
t
ly
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e
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t
o
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re
m
b
a
n
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
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m
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il
:
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ima
n
a
m
in
5
4
1
@g
m
a
il
.
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o
m
.
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fr
i
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n
ita
Da
h
l
a
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As
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P
ro
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g
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se
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stit
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h
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re
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iv
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n
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g
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g
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n
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ics
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).
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re
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tri
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l
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sig
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l
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at
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o
lar
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se
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rc
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In
stit
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te (S
RI),
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i
v
e
rsiti
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n
o
l
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g
i
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ARA
(UiTM
),
M
a
lay
sia
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
sa
id
a
tu
l
h
a
b
sa
h
9
3
@g
m
a
il
.
c
o
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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t J Ad
v
Ap
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l Sci
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N:
2252
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8
8
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imi
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v
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ti
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ll
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g
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th
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m
b
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.
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e
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rn
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h
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.
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in
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n
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g
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g
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n
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ra
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c
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se
tt
s
In
stit
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h
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IT)
,
USA.
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re
se
a
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c
a
n
b
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c
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tac
ted
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m
a
il
:
M
Ha
ss
a
n
@u
n
it
e
n
.
e
d
u
.
m
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.